Data analytics provide in depth information and understanding into a data corpus
Simply stated, analytics is the discovery, interpretation, and communication of meaningful patterns in data. Analytics are particularly valuable when applied to large databases that are “rich” or dense with recorded information. In order to make sense of millions of data points, analytics relies on the simultaneous application of statistical models, computer programing and operations research to provide data aggregations that can then be interpreted by trained personnel. Effective analytics rely heavily on data visualization displays to communicate insight. Humans are extremely visual and well designed visualizations quickly provide information effectively. Organizations may apply analytics to business data to describe, predict, and improve business performance. Since analytics can require extensive computation, the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics. The legal environment, with its constantly changing components and variables, may seem like an area where it is difficult to quantify activity and results. Corporate legal departments often have numerous offices in various geographies, a number of divisions and non-standardized processes for matters—all making legal data collection, analysis and comparison very challenging. Data analytics can be used directly in the eDiscovery process or by law firms to help them improve their performance in the market.
Traditionally, lawyers have competed in the marketplace by combining three key legal skills: legal research, experience and reasoning, used in combination to convince clients that they are the best choice for a litigation matter. Adding legal analytics to the arsenal enables lawyers to gain critical advantage in both the business and practice of law. Data analytics mine litigation data from a wide variety of sources, revealing insights not available before concerning judges, lawyers, courts and litigation matters themselves. This information can then be used to help the team make calculated judgments about the current litigation. Business analytics is a separate use case of analytics for law firms to consider.
Over the last 2 years, there has been a focus on the use of analytics to perform predictive coding (the machine learning using a set of seed documents to train an algorithm in iterative fashion to recognize patterns of relevance) in order to cull documents for production during the discovery process. However, there is a wide range of available analytical tools beyond predictive coding, and they are often built into complete eDiscovery platforms. Plaintiffs can used analytic tools to evaluate the strength of a case and when or whether to file. Defendants use analytic tools during early case assessment to develop a case strategy, to test search terms and identify the best analytical tools to use for discovery purposes and to analyze documents received from another party. Injecting analytics into an eDiscovery workflow will improve results and cut costs. Early Case Assessment has been brought back to the forefront of litigation determination. (See Early Case Assessment for details). Following are five primary ways that analytics can drive better decision-making and therefore lead to improved litigation outcomes:
- Define Outcomes
- Increase Efficiency
- Greater Control
- Better Case Decisions